Exploring Compassionate Care Patterns Among Nurses and Its Associations With Resilience: Multilevel Contextual Effects Modeling.

Compassionate care and resilience play crucial roles in enhancing care quality. Understanding compassionate care patterns in the nursing population and their relationship with resilience can improve knowledge of these concepts. To investigate compassionate care patterns among Iranian nurses and their associations with resilience at individual and contextual levels. This cross-sectional study used Persian versions of the 28-item Compassionate Care Questionnaire (CCQ) and Connor-Davidson Resilience Scale (CD-RISC). 478 Iranian nurses from 19 wards across 16 hospitals in northern Iran participated between February and September 2023. Latent profile analysis (LPA) was performed on compassionate care dimensions. Multilevel logistic regression modeling explored associations between resilience dimensions and compassionate care profiles, adjusting for control variables at individual and contextual levels. LPA revealed two distinct compassionate care profiles: "Low Compassionate Care" (16.3%) and "High Compassionate Care" (83.7%). After adjusting for control variables, personal competence (OR = 1.09, 95% CI: 1.02-1.15), positive acceptance (OR = 1.23, 95% CI: 1.06-1.44), and spirituality (OR = 1.17, 95% CI: 1.01-1.38) were associated with higher odds of inclusion in the "High Compassionate Care" profile. The empty model showed that 6.5% of compassionate care patterns were explained at the ward level. After adding predictors at individual and ward levels, explained variances were reduced to 1.5% and < 0.01%, respectively. This study offers insights into compassionate care among nurses, showing that few exhibited "Low Compassionate Care." Higher resilience was positively linked to elevated compassionate care levels. Policymakers, managers, and educators can leverage these findings to enhance nursing management and support systems by prioritizing resilience-building strategies, ultimately improving patient care quality.